The Potential Impact of Coinfection on Antimicrobial

Home , Coinfection

Review

The potential impact of coinfection on

antimicrobial chemotherapy and drug resistance

1* 2,3* 4 5 6

Ruthie B. Birger , Roger D. Kouyos , Ted Cohen , Emily C. Grifﬁths , Silvie Huijben ,

1,7 8 1,9 1,9*

Michael J. Mina , Victoriya Volkova , Bryan Grenfell , and C. Jessica E. Metcalf

Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA

Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zu¨ rich, University of Zu¨ rich, Zu¨ rich, Switzerland

Institute of Medical Virology, University of Zu¨ rich, Zu¨ rich, Switzerland

Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA

Department of Entomology, Gardner Hall, Derieux Place, North Carolina State University, Raleigh, NC 27695-7613, USA

ISGlobal, Barcelona Ctr. Int. Health Res. (CRESIB), Hospital Clı´nic –Universitat de Barcelona, Barcelona, Spain

Medical Scientist Training Program, Emory University School of Medicine, Atlanta, GA, USA

Department of Diagnostic Medicine/Pathobiology, Institute of Computational Comparative Medicine, College of Veterinary

Medicine, Kansas State University, Manhattan, KS, USA

Fogarty International Center, National Institutes of Health, Bethesda, MD, USA

Across a range of pathogens, resistance to chemothera- One way to classify the diversity of possible interactions

py is a growing problem in both public health and animal between pathogens is to set them on a spectrum of syner-

health. Despite the ubiquity of coinfection, and its po- gistic to antagonistic. In synergistic interactions, the with-

tential effects on within-host biology, the role played in-host growth rate of one parasite will increase in the

by coinfecting pathogens on the evolution of resistance presence of the other, while in antagonistic interactions,

and efﬁcacy of antimicrobial chemotherapy is rarely the presence of one pathogen will limit the growth rate of

considered. In this review, we provide an overview of the other. Examples of the former might include HIV–

the mechanisms of interaction of coinfecting pathogens, hepatitis C virus (HCV) [4] and HIV–malaria [5–7]; exam-

ranging from immune modulation and resource modu- ples of the latter might be multiple strains of malaria [8]. It

lation, to drug interactions. We discuss their potential is also possible that coinfecting pathogens do not interact,

implications for the evolution of resistance, providing but as this is unlikely to affect the evolution of resistance it

evidence in the rare cases where it is available. Overall, is not discussed further in this review. It should be noted,

our review indicates that the impact of coinfection has however, that the degree to which pathogens interact is

the potential to be considerable, suggesting that this

should be taken into account when designing antimicro- Glossary

bial drug treatments.

Coinfection: for the purposes of this review, the term coinfection is used in a

broad sense, covering all combinations of infection with more than one

Classifying mechanisms of pathogen interactions

pathogen or strain. We consider coinfections with multiple strains of the same

The spread (see Glossary) of chemotherapy-resistant species as well as infections with multiple species of pathogen (following [48]).

This includes simultaneous infection (two pathogens or strains transmitted

pathogens is a serious global problem [1], affecting our

together), superinfection (one pathogen or strain infects a host where another

ability to control pathogens ranging from parasites to

is already present), and sequential infection (one pathogen or strain infects

viruses. Infected individuals are often coinfected, either after a previous infection has cleared, potentially leaving residual changes in

the immune or resource landscape that would affect the second pathogen).

by multiple strains of the same pathogen or by different

Emergence: the emergence of a resistance mutation within a pathogen is

species of pathogen. Classic examples include the multi-

generally the result of a de novo mutation. For bacteria, other possibilities

plicity of strains typically identiﬁed in malaria infections include acquisition from other strains or species present in the vicinity of the

pathogen, that is, via horizontal gene transfer.

[2] and coinfections involving human immunodeﬁciency

Fitness cost: frequently, mutations conferring some degree of resistance are

virus (HIV) and Mycobacterium tuberculosis (TB) [3]. Here, associated with a fitness cost in terms of reduced pathogen within-host growth

we present an overview of the potential ways by which rate, which translates into a reduction in transmission of the resistant pathogen.

Such costs are often mediated by competition with other coinfecting pathogens,

coinfection might affect the outcome of chemotherapy,

via direct competition, or apparent competition mediated by the immune system.

focusing on the question of the evolution of drug resistance. Even mutations that apparently have no cost, for example, mutations involved in

conversion of efflux pumps, will be affected by the presence of susceptible

Corresponding author: Birger, R.B. ([email protected]). strains, purely in the fraction of transmission dominated.

Keywords: drug resistance; coinfection; immune modulation; resource competition; Focal pathogen: we use the term focal pathogen to mean the pathogen initially

parasite interactions. targeted for treatment. Often, but not always, this can mean the pathogen

These authors contributed equally. causing either more severe or more recognizable disease.

Spread: once a de novo resistance mutation has emerged, it must spread

0966-842X/

within the population. This requires both successful replication within a host,

and then spread through the population via transmission to other hosts.

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Review Trends in Microbiology September 2015, Vol. 23, No. 9

Table 1. Interactions at the scale of the individual

Beneﬁcial Neutral Detrimental

Beneﬁcial HIV–HCV [4] Helminths beneﬁcial for bacteria/viruses [17,18] Cheating/cooperation in siderophore-sharing bacteria [28,29]

c d

HIV–TB [3] HIV–GB virus C (detrimental to HIV) [74]

Neutral – Non-overlapping: tinea pedis, inﬂuenza Fever-promoting: malaria detrimental for syphilis[75],

Helicobacter pylori restricting (detrimental for) TB infection [26]

Detrimental – – Competing strains: malaria (depending on strains) [38]

Row labels correspond to the impact on one pathogen of the coinfection, while column labels correspond to the impact of the coinfection on the other.

Hepatitis C virus. c

Mycobacterium tuberculosis.

Formerly known as Hepatitis G virus or HGV.

often unclear, and the available evidence is possibly con- Synergistic interactions: immune-mediated facilitation

troversial. The type of interaction broadly determines the When coinfection occurs, one or both pathogens may sup-

impact of coinfections on resistance evolution: while syn- press the immune response. This suppression may facili-

ergistic interactions tend to promote resistance, antago- tate the spread of drug-resistant mutants of the coinfecting

nistic interactions hinder the evolution of resistance (see pathogen via several routes. First, reduced immune-medi-

below). ated killing of pathogens may lead to higher pathogen

This review is organized around the two main mecha- replication, which can increase the probability of the emer-

nisms that might shape the outcome of chemotherapy: (i) gence of de novo resistance (e.g., HIV–malaria coinfection

immune modulation (whereby the presence of the coinfect- [5]). Second, the reduced efﬁcacy of the immune system

ing pathogen can affect immune function), and (ii) resource may increase the frequency of symptomatic infections (in

modulation (where the coinfecting pathogen can have the absence of immunopathology) and hence the use of

effects on resource availability for the focal pathogen) – antimicrobials (e.g., HIV–herpes simplex virus 2 coinfec-

Table 1 and Figure 1 give examples. For both mechanisms, tion [9]), which will increase the selective pressure for

we provide an overview of their potential to affect the resistant mutants and potentially the spread of resistant

emergence and spread of drug resistance across a range pathogens. Third, reduced immune-mediated killing may

of pathogens, distinguishing between synergistic and an- allow the replication of drug-resistant strains bearing a

tagonistic interactions where possible. It is important to high ﬁtness cost (which would otherwise be outcompeted

note that for many pathogens, multiple mechanisms may by ﬁtter sensitive strains, e.g., HIV–TB coinfection [10]).

apply; additional, less clearly classiﬁed mechanisms may Similarly, impaired immune control may increase the

also be involved (Boxes 1 and 2). Finally, while there may danger of a recrudescence of partially resistant pathogen

be clear evidence of interaction, the exact mechanism in populations after therapy has ended. Such partially resis-

play is frequently unknown. tant pathogen populations are often selected for during

therapy, and might be present after treatment [11]; with

Immune modulation an effective immune response they would be rapidly elimi-

Pathogens attacking hosts are confronted by the immune nated, but an immunosuppressive coinfection may allow

system, and often the immune responses stimulated by one for their proliferation [12]. The impact of HIV coinfection

pathogen interact with those stimulated by a coinfecting on drug-resistant TB and malaria, on which recent major

pathogen. This type of interaction can be either synergistic strides in research have been made, are classic examples

or antagonistic, depending on pathogen identity and type of how an immunosuppressive pathogen can exacerbate

of immune response. resistance problems.

HIV and malaria

Coinfecng malarial strains HIV and TB

Resource compeon , cross-immunity) ( (Immune-mediated facilitaon)

S. pneumoniae S. aureus & Sideropho re-sharing bacteria

(Resource compeon) (Resource cooperaon) C. difﬁcile & gut microﬂora Upper respirato ry tract bacterial & viral (Resource compeon) infecons

Pseudomonas & S. aureus (Resource cooperaon)

(Direct compeon) Helminths & microparasites

H. pylori & Vibrio cholerae (Immune-mediated facilitaon)

(Immune-mediated compeon) Antagonisc Neutral Synergisc

TRENDS in Microbiology

Figure 1. Antagonistic to synergistic coinfections. Coinfection can have effects on focal pathogen density and replication. Different interactions, ranging from antagonistic

to synergistic, can then have differing effects on chemotherapy and resistance. Species referred to in the figure: Streptococcus pneumoniae, Staphylococcus aureus,

Clostridium difficile, Pseudomonas sp., Helicobacter pylori and Vibrio cholerae. Abbreviation: TB, Mycobacterium tuberculosis.

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Box 1. Direct interactions ﬁtness thresholds [10] (allowing the spread of resistant

strains with low ﬁtness), and reduced drug absorption of

Competition:

anti-TB drugs in the presence of HIV [15] (facilitating

Most examples in this review involve indirect pathogen interac-

tions via a third pathway. Pathogens, however, may also enter into selection for partially resistant strains).

direct, or interference competition [46] by actively synthesizing For malaria, it has been suggested that an HIV-mediated

molecules that attack competitors. Examples include bacteriocins

increase in replication of the malaria parasite promotes

for bacterial species [76] (such as the serine protease Esp produced

de novo resistance [5]. Indeed, an increased prevalence of

by Staphylococcus epidermidis competing with pathogenic Staphy-

resistant malaria parasites has been found in HIV-positive

lococcus aureus in nasal cavities [77]); pyruvate in competing

strains of trypanosomes [53]; the reactive oxygen species produced versus HIV-negative pregnant women [16]. The mecha-

by Enterobacter bacteria that impede development of Plasmodium

nisms promoting malaria drug resistance in HIV-coinfected

falciparum within mosquitoes [78]; and inhibition of adhesion to

hosts are expected to be similar to those promoting TB

intestinal mucus glycoproteins between gut bacteria [79]. Such

drug resistance in HIV–TB infections, but evidence is

attacks may reduce the numbers of competitors but may also

directly supply resources, as when Pseudomonas aeruginosa lyses largely lacking.

S. aureus and exploits the resulting released iron [80]. Again, if Although HIV presents a rather extreme case of im-

drug-sensitive coinfecting pathogens directly attack drug-resistant

mune modulation, coinfections with other pathogens can

mutants, aggressive chemotherapy against the pathogens will tend

have similar effects on the efﬁcacy of chemotherapy and

to amplify the growth rates of resistant mutants.

the evolution of drug resistance. For instance, it has been

Horizontal gene transfer:

Pathogens can also directly interact through horizontal gene shown that helminth species that suppress the interferon-

transfer (HGT), that is, the exchange of genetic material between g (IFN-g) response lead to a higher pathogen load of

different strains or species. HGT requires coinfection or co-coloniza-

coinfecting microparasites in mice [17]. Recent work, also

tion of the treated pathogen with commensal microflora. In the case

in mice, has indicated that helminths can impair antiviral

of between-strain transfer, resistance genes can be transferred from a

immunity directly, and that these effects can be long-lived

resistant strain to a previously sensitive strain. This can increase the

speed with which resistance mutations spread, facilitate multidrug and have implications for individual- and community-level

resistance, increase the pool of resistance genes or mutations, and resistance ecology [18]. In humans, measles infection can

provide a reservoir for persistence of resistance genes.

considerably suppress the immune system, thereby in-

Conversely, resistance mutations found at high densities in the

creasing the pathogenicity of coinfecting microbes [19,

microflora, coupled with HGT capacities of many key pathogens,

100]. Similarly, malaria infections in young children are

suggest that the commensal microflora could be an important

source and sink of resistance [81–85]. associated with an increased risk of invasive bacterial

This implies that the control of a pathogen does not necessarily

infections, possibly through malaria-induced spleen dys-

lead to control of resistance. However, the impact of the complex-

function [20]. Lastly, epithelial cell damage and/or dys-

ities (e.g., plasmid transfer dynamics [86–93]) of cross-species

functional innate immune responses triggered by inﬂuenza

resistance transfer is understudied.

infections may cause a transiently elevated incidence of

For TB, Dye et al. [13] suggest several mechanisms for bacterial coinfections [12,21]. Such coinfections, in turn,

why HIV coinfection increases the risk of drug resistance, may increase the need for antibiotics, particularly follow-

including increased mycobacterial burden [14] (causing an ing a primary disease episode, and thus increase potential

increased risk of de novo resistance mutations), lower selection for resistance.

Box 2. Drug-mediated interactions

Drug-mediated complications in treating coinfected patients can are able to reduce antibiotic concentrations both intracellularly and

affect the evolution of resistance in various ways. Here we focus on across the biofilm, for example, through reduced outer membrane

collateral selection of resistance linked to nontarget pathogens. permeability [96], or indirectly through inflammation [97]: inflamma-

Collateral selection occurs when treatment of a focal infection tory fluids have low pH, and some antibiotics are less active in acidic

selects for resistance in other pathogens or commensal colonizers. conditions. Reducing drug concentrations can facilitate resistance

This occurs either because a competitor is removed or because the evolution in both the focal pathogen and collateral selection for

selective pressure promotes de novo resistance in the coinfecting resistance in any other local infection.

pathogen. For many bacterial pathogens, collateral selection is a One viral example of a collateral effect is the tenofovir-mediated

major mechanism of selection for resistance [84]. This is the case for HIV–hepatitis B virus (HBV) interaction [98]. Tenofovir is effective in

several reasons. First, most bacterial pathogens typically colonize treating both viruses and is often used as part of triple-antiretroviral

their host asymptomatically (e.g., Staphylococcus aureus and Strep- therapy for HIV. This is often unproblematic and helpful for treating

tococcus pneumoniae). Accordingly, symptomatic infections play both infections. However, the other drugs in this combination are less

only a small role in pathogen transmission, and treatment targeted at (or not at all) effective against HBV, so combination therapy for HIV

symptomatic coinfecting pathogens causes only a relatively weak may only be monotherapy for HBV. Such a suboptimal genetic barrier

selective pressure for resistance evolution in the focal pathogen. for HBV may eventually select for HBV resistance rather than curbing

Second, many antibiotics (especially broad-spectrum drugs) are HBV infection.

prescribed for many conditions and inhibit the growth of various A similar example comes from HIV–malaria coinfection. Daily

pathogens. Antimicrobials reaching lethal concentrations for the prophylaxis with cotrimoxazole (CTX) is recommended for HIV-infected

target pathogen may be less lethal or only bacteriostatic for other patients to prevent opportunistic infections. As the drug acts on the

bacteria, allowing the latter to acquire resistance. For instance, same pathway as the antimalarial sulfadoxine–pyrimethamine (SP),

antimicrobial treatments can increase resistance in enteric bacteria, daily CTX treatment selects for SP-resistant parasites[6,7]. Moreover,

as antimicrobial concentrations in the intestine differ from those in pharmacokinetic interactions between antiretroviral therapy and com-

the target organ [94], and the enteric bacteria can differ from the bination-based antimalarial drugs are reason for concern since these

pathogen in drug susceptibility. Third, resistance genes can be interactions can cause either increased or decreased drug bio-

genetically linked [95], and hence hitchhiking can increase resistance. availability of antimalarial effect, thereby potentially increasing the risk

Lastly, some bacteria (especially those capable of forming biofilms) of selection for drug resistance (reviewed in [99]).

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Another possible mechanism of immune manipulation by behavior may decline with the spatial scale of competition

the ﬁrst-arriving pathogen is illustrated by superinfections [29]). Assistance provided by a coinfection may also be a

with two TB strains: in vivo experiments have suggested byproduct of other processes. Several studies have sug-

that superinfecting TB strains are shuttled to pre-existing gested that upper respiratory tract viral infections predis-

granulomas caused by prior TB infections. In these granu- pose hosts to bacterial respiratory infections, in part, by

lomas, the new infecting cells may avoid immune surveil- improving adherence of bacteria to epithelial cells or by

lance. Local competition between strains may also occur, exposing basement membrane proteins useful for bacterial

but this phenomenon does seem to assist the superinfecting binding for both human infections [30,31] and animal

strain in evading the immune response [22]. infections [32]. Alternatively, viral infections can facilitate

More generally, most pathogens evade the immune bacterial ones by producing substrates beneﬁcial to bacte-

system, and many of them do so by impairing its function rial growth [33]. A secondary infection may also catalyze

rather than by simply escaping recognition [23]; recent transition of a primarily commensal organism to a patho-

research has shed better light on the underlying mecha- genic state. For example, bacterial colonization and bioﬁlm

nisms [11,12,19,22]. The quantitative contribution of these formation often require stringent downregulation of viru-

perhaps transient immune-suppressive effects on the re- lence factors in order to facilitate evasion of the host’s

sistance problem remains an open question; however, sim- immune system. Thus, colonizing bacteria rarely express

ilar (albeit weaker) effects than those observed for the virulence factors sufﬁcient to promote invasion [34]. In the

HIV–TB interaction (increased antibiotic consumption, setting of a secondary viral infection, however, virus-

increased pathogen loads, lower ﬁtness thresholds) are induced pyrogenic cytokine secretion often results in a

likely to occur in other systems as well. hyperthermic state that may induce bioﬁlm dispersion

and expression of bacterial virulence proteins, increasing

Antagonistic interactions: immune-mediated the likelihood of invasion [35]. More generally, inasmuch

competition as the coinfecting pathogen may increase the growth rate of

Interaction with the immune system does not necessarily the focal parasite, it may also assist spread of resistance

lead to synergistic interactions between coinfecting patho- mutations by facilitating replication and thus increase the

gens. If the two coinfecting species or strains are antigeni- risk of de novo mutations arising.

cally or immunologically similar enough, the immune A key resource for invading pathogens is the available

response to one strain or species may suppress the other. habitat. Many interactions can lead to one pathogen spe-

Examples of this type of interaction include different cies creating habitat availability for another. Bioﬁlm de-

strains of Streptococcus pneumoniae [24] and the interac- velopment by bacterial species colonizing a wound [36] is

tions between strains of the rodent malaria parasite Plas- one such example. As above, by increasing the density of

modium chabaudi [25]. In such cases, the immune system the focal pathogen, such mechanisms imply that coinfec-

mediates ‘apparent competition’, that is, the abundances of tions can increase the spread of resistance. This effect is

two pathogens are inversely correlated, as is the case for potentiated when bioﬁlms protect the residing bacteria

classic competition. It is also possible for pathogens to from antibiotic agents (e.g., by limiting drug penetration),

induce immune responses to unrelated pathogens. For which can lead to suboptimal focal drug availability, facili-

example, there is some evidence that Helicobacter pylori, tating the evolution of resistance [37].

which can be a commensal, induces antibacterial immune Competitive facilitation (i.e., the presence of a coinfect-

responses that can suppress coinfecting pathogens such as ing strain increasing the biomass of the focal strain) is

TB or Vibrio cholerae [26]. The impact on the evolution of observed in certain rodent malaria strain pairs [38]. Some

resistance is likely to be complex and context-dependent, evidence of competitive facilitation of drug-resistant Plas-

but in most cases such interactions should limit the evo- modium falciparum strains is also reported in women

lution of resistance unless treatment clears the competing following intermittent preventive therapy during pregnan-

pathogen. In the latter case, we might expect increased cy (IPTp) in Tanzania [39]. Uncertainty remains as to

selection for resistance since the total antagonistic pres- whether the main mechanism behind these observations

sure on the focal pathogen would be reduced, potentially is immune- or resource-driven. The immune-mediated

leading to suboptimal drug dosage [8,27]. interaction may be present if cross-immunity is not fully

overlapping: one strain could beneﬁt from the focus of the

Resource modulation immune system on the coinfecting strain [40]. The re-

Pathogens exploit a diverse array of host resources (e.g., source-modulation interaction may be present because

cells, tissue, and metabolites). Their survival and growth different malaria strains can prefer red blood cells of

depends on efﬁcient acquisition of these resources, which different ages and therefore may provoke different levels

can be either hindered or helped by coinfecting pathogens. of red blood cell production [41,42]. The presence of a strain

that preferentially targets older red blood cells could stim-

Synergistic interactions: resource cooperation or ulate production of younger red blood cells, which might

indirect support beneﬁt a competitor (competitive facilitation), although

The presence of a coinfection may assist the focal infection clearly the reverse (competitive suppression) is also a

in its acquisition of resources. For example, many bacteria possibility. Again, increased abundance provides an oppor-

engage in mutualistic behaviors such as siderophore pro- tunity for either the appearance of a de novo resistance

duction, which assists the whole bacterial population in mutation or the persistence of resistance mutations with

iron-scavenging behaviors [28] (although note that this lower ﬁtness.

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Finally, a special type of resource modulation exists for attributable to localized resources available on a ‘ﬁrst-

infections that use immune system cells as a resource. The come, ﬁrst-served’ basis [54]. Reduction of focal pathogen

presence of a coinfection may increase the abundance of ﬁtness in the face of exploitation competition by coinfecting

target cells, and thus aid the focal infection. For example, pathogens implies that aggressive chemotherapy [55],

the presence of malaria, TB, or HCV may stimulate the which eliminates competing strains, may facilitate the

production of target cells for HIV or stimulate viral repli- spread of resistance.

cation [7,43,44] and thereby potentially promote the evo- A variation on the theme of exploitation competition can

lution of resistance. emerge when the resource of the focal pathogen proves to

be a component of the immune system downregulated by

Antagonistic interactions: resource competition the coinfecting pathogen, rather than a direct resource for

A resistant mutant of a focal pathogen may pay a ﬁtness the latter. The net result is the same – the focal pathogen

cost in the presence of a coinfecting pathogen by being may have a lower replication rate as a result of the im-

outcompeted in the acquisition of resources [45]. This pro- mune-modulatory activity of the ﬁrst (e.g., measles–HIV

cess, termed exploitation competition, may reduce the coinfection [56]). This would reduce the potential for the

resistant mutant’s within-host growth rate, density, or spread of resistance in the focal pathogen.

persistence [46]. The mechanism may be mediated by

the effect of the mutation on enzymes with biologically Concluding remarks

important functions, since these are generally the targets Current thinking in chemotherapy and resistance-man-

of drugs [47]. The magnitude of the effect is likely to depend agement of infectious diseases usually focuses on one

on the degree of resource-niche overlap between the focal pathogen at a time. By contrast, the examples from recent

and coinfecting pathogens, or the ﬁtness advantages and research provided here demonstrate the importance of

abundance of a mutant strain relative to conspeciﬁcs in the taking into account interactions between pathogens and

case of multistrain infection [48]. For example, two patho- with commensal species in the microﬂora. Coinfections can

gens with very different target cells (e.g., epithelial cells make the outcome of treatment decisions context-speciﬁc,

versus erythrocytes) are unlikely to enter into exploitative implying that optimal treatment policies may depend on

competition. By contrast, two different strains of malaria the abundance of other pathogen species or strains (either

parasites, both targeting red blood cells of similar age and within the treated host or in the host population) as well

type, may be in direct competition; further examples of as on drug-mediated interactions (Box 2). As we outline

direct competition are given in Box 1 [8,49]. This also above, outcomes in terms of both pathogen abundance and

illustrates that the degree of competition may vary over resistance evolution will be mediated by the degree to

the time-course of an infection as key resources are deplet- which interactions are synergistic or antagonistic. The

ed [42]. understanding of the mechanisms underlying these inter-

A consequence of resource competition is that vaccina- actions remains limited, but it can have major applied

tion or chemotherapy that controls the pathology but does consequences. For a particular set of mechanisms, the

not eliminate the focal pathogen may prevent entry or outcome might be highly predictable, given the identity

suppress replication of a coinfecting pathogen. In other or mode of the two pathogens (such as HIV coinfection

words, a drug treatment regime that does not fully clear reducing the ability of the immune system to ﬁght off

the drug-sensitive strain could be able to control the resis- opportunistic infections). Alternatively, factors such as

tant strain. This principle has been demonstrated in rodent host immunity, order of pathogen arrival, or bacterial

malaria infections [8]. Similarly, epidemiological and exper- mode (e.g., commensal or pathogenic) could have major

imental evidence suggests that well-controlled Eimeria in- effects on the direction of the interaction, immediately

fection in chickens can reduce Salmonella due to the multiplying the number of components that need to be

inﬂammatory and immune mucosal responses in the intes- understood before one can begin to delineate the outcomes

tinal compartments shared by the pathogens (reviewed in of treatment decisions for either patient health or evolu-

[50]). These phenomena highlight the complexity of com- tion of resistance. For example, there is evidence that

petitive interactions, and how resource and immune mech- H. pylori coinfection can both help and hinder cholera

anisms can play intertwined roles in coinfection systems. coinfection in its pathogenic and commensal modes, re-

A range of in vitro studies have provided evidence for the spectively [26]. This is further complicated by the potential

operation of exploitation competition [49] – for example, for complex nonlinear outcomes inherent in infectious

drug-sensitive M. tuberculosis strains outcompeting rifam- disease dynamics, which might even lead to changing

pin-resistant mutants [51]. While these studies provide directions of outcomes over the course of an infection at

proof-of-concept for exploitation competition, extrapolat- the individual scale – and unpredictable links between

ing ﬁtness costs from in vitro to in vivo may be problematic coinfection at the individual scale and pathogen coexis-

(e.g., [52]). Evidence of competition is harder to obtain in tence at the population scale [57].

vivo because the impacts of immunity and competition may One key challenge is to predict population-level conse-

be hard to distinguish [53]. A solution is to use perturba- quences from mechanistic interactions in individual hosts

tions of immunity and explore the impact that this has [58,59]; or, in the opposite direction, to interpret ecological

on performance of single infections and coinfections patterns of co-occurrence as evidence for within-host mecha-

[54]. This type of experiment has indicated, for example, nisms. An example for these challenges is provided by

poor competitive ability of colonizing resistant Staphylo- the HIV–TB interactions. Small epidemiological studies

coccus aureus strains in the presence of a resident strain, have shown strong local associations between HIV and

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Box 3. Outstanding questions system to study rapid adaptive evolution in response to

treatment [70].

How can we predict population-level consequences from mechan-

To conclude, it seems clear that coinfection is likely to be

istic interactions at the within-host level?

What is the optimal order of treatment of coinfecting pathogens? an important modiﬁer in the evolution of resistance. How-

Should treatment be intensified in the presence of an immuno- ever, the degree to which coinfecting pathogens interact

suppressive coinfection to compensate for the impaired killing by

remains unclear in many cases; and even where we know

the immune system? What consequence does this have for

that interactions are occurring, the mechanisms are often

resistance evolution?

poorly deﬁned. Improvements in laboratory technology

Should research and development of new drugs be focused on

treatment of specific very common coinfections? (e.g., whole-genome sequencing) and bioinformatic analy-

At the population scale, should coinfected individuals be prior-

sis will facilitate the exploration of currently unknown

itized for treatment when there are limited resources?

quantities such as the prevalence of multistrain infection

in various pathogens, and some mechanisms of resistance

drug-resistant TB (e.g., [60]), and have shown that small acquisition may become clear with further technical

HIV-positive populations can support the spread of a low- advances. The challenge then becomes translating knowl-

ﬁtness drug-resistant TB strain [61]. Interestingly, however, edge of interactions into treatment options. An array of

there is currently limited larger-scale ecological evidence for unconventional opportunities may emerge with better

the association of HIV with multidrug-resistant TB [62] – knowledge of the underlying mechanisms. For example,

perhaps due to HIV-stimulated reactivation of older, nonre- inﬂuenza and streptococcal infections interact in a way

sistant TB strains, and population-level competitive disad- that is detrimental to human health, and the mode of their

vantage of drug-resistant TB strains evolving in HIV- interaction suggests that mechanisms that repair the epi-

positive individuals [63]. Additionally, sometimes within- thelial cell wall, and thus reduce the effect of previous

host and population-level dynamics can be at odds when it inﬂuenza infection by preventing one mechanism of inter-

comes to interventions: a recent study in African buffalo action, might enable the avoidance of spread of drug resis-

showed that anthelminthic treatment improved survival tance. Fecal transplants present another unconventional

rates after bovine TB infection, but exacerbated TB trans- opportunity: thus far, they seem to be very successful in

mission [57]. These examples highlight the nontrivial rela- treating some bacterial infections [71], and also, of most

tion between mechanistic interactions in individual hosts relevance here, they show promise for treatment of antibi-

and population-level signatures; ecological data provide an otic-resistant infections [72]. Similarly, recent advances

important piece of evidence for the impact of coinfections, and in tapping the potential of uncultured bacteria have led to

hence future public health and ecological research efforts the development of the antibiotic teixobactin, which shows

should be optimized for the interpretation of such data. promising refractoriness to resistance [73]. More classical-

An important consequence of these uncertainties is that ly, better treatment strategies may be suggested by this

while it is clear that coinfection may necessitate coordina- information; for example, for coinfections such as HIV–

tion of treatment policies between pathogens, many im- malaria, identifying the interaction mechanisms may in-

portant questions still remain unanswered for many form improvements in treatment, such as guiding research

pathogen combinations (Box 3). Coinfected individuals toward an alternative for cotrimoxazole (CTX) that does

may be in worse health than those with single infections not select for antimalarial resistance, or one that encom-

[64], and may also pose the biggest risk of transmission to passes the function of CTX and IPTp (prophylactic treat-

others (as shown in buffalo [65] and mice [66]). By contrast, ment against malaria during pregnancy). Generally,

the chemotherapy in these patients may pose a higher risk understanding in which direction and by which mecha-

for resistance mutations and propagation, and coinfected nisms pathogen communities evolve in response to antimi-

individuals may be ineligible for treatment because of their crobial therapy may be vital for both the design of

comorbidities [67]. pharmaceuticals and maximizing the efﬁcacy of clinical

Many other areas of biology also wrestle with issues of measures.

evolution of resistance in complex multispecies communi-

ties, in particular agricultural science and resistance in Acknowledgments

herbicide and insecticide deployment [68]. For instance, This work emerged from a meeting funded by the RAPIDD program of the

Science & Technology Directorate. RAPIDD is administered by the Depart-

the source-sink dynamics of biological invasion of resistant

ment of Homeland Security and the Fogarty International Center, National

weeds to neighboring ﬁelds is an agricultural example of

Institutes of Health; Science and Technology Directorate, Department of

the spread of resistance to untreated hosts, and the com-

Homeland Security; contract HSHQDC-12-C-00058. We would like to thank

plexity of cross-scale resistance dynamics. Similar pat- the other attendees at the meeting not represented in the author list for their

terns of unintentional human-mediated selection occur, valuable contributions to discussions. RBB is supported by the Department

of Ecology and Evolutionary Biology at Princeton University. RDK is funded

wherein efforts to encourage growth in crops can spill over

by the Swiss National Science foundation (SNSF #PZ00P3_142411). TC is

and impact weed evolution and the structure of the crop-

supported by NIH U54GM088558 from the National Institute of General

pest community [68]. Also, a similar debate on optimal

Medical Sciences; the content is solely the responsibility of the authors and

herbicide treatment, low dose versus high dose, is being does not necessarily represent the ofﬁcial views of the National Institute of

held in agriculture, having parallel foundation in resource General Medical Sciences of the National Institutes of Health. SH was funded

by the Society in Science – Branco Weiss Fellowship and Marie Curie IIF

competition between herbicide-resistant and herbicide-

Fellowship. VVV is supported through the Institute of Computational

susceptible weeds [69]. There may be opportunities to

Comparative Medicine at the College of Veterinary Medicine of Kansas State

exchange expertise between ﬁelds; indeed, agricultural

University. BTG is supported by the RAPIDD program of the Science and

systems may even provide an excellent economic model Technology Directorate, Department of Homeland Security, the Fogarty

542

Review Trends in Microbiology September 2015, Vol. 23, No. 9

International Center, National Institutes of Health. CJEM is funded by the 25 Fairlie-Clarke, K.J. et al. (2013) Quantifying variation in the potential

Bill and Melinda Gates Foundation. for antibody-mediated apparent competition among nine genotypes of

the rodent malaria parasite Plasmodium chabaudi. Infect. Genet.

Evol. 20, 270–275

Appendix A. Supplementary data

26 Lin, D. and Koskella, B. (2014) Friend and foe: factors inﬂuencing the

Supplementary data associated with this article can be found, in the online

movement of the bacterium Helicobacter pylori along the parasitism–

version, at doi:10.1016/j.tim.2015.05.002.

mutualism continuum. Evol. Appl. 8, 9–22

27 Kam, Y. et al. (2014) Evolutionary strategy for systemic therapy of

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